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What does coefficient mean for a binary independent variable in multiple linear regression?

0

$begingroup$

Let's say I have a multiple linear regression model where my dependent variable, Y, is an integer. And, one of my independent variables --x1-- is binary --let's say either 0 or 1.

We know that sign of the coefficient for x1 in the model, positive or negative, demonstrates its correlation with Y. My question though is, is there anyway for us to know that what the correlation of x1 values independently, 0 or 1, is with the dependent variable? For instance, do we know if that 0 is the reason for the sign of coefficient and the more 0 will lead to more Y (not sure if this is the correct language but hope you understand what I am saying.)

A real-world example, I have a multiple linear regression model to find the correlation of a set of numeric indexes in tweets, as independent variables, with the number of retweets as dependent variable. One of the independent variables in this model is the tweet's fact checking label, "true" or "false" which we call it "truth_label." I have trained a multiple linear regression model and the coefficient of the truth_label is positive meaning that it has a positive correlation with the number of shares. But, I would like to know if that positive correlation is because of the "true" values or "false" values. Hope this example made my question a bit more clear.

linear-regression correlation

share|improve this question

asked 23 mins ago

PedramPedram

1012

$endgroup$

add a comment | 

0

$begingroup$

Let's say I have a multiple linear regression model where my dependent variable, Y, is an integer. And, one of my independent variables --x1-- is binary --let's say either 0 or 1.

We know that sign of the coefficient for x1 in the model, positive or negative, demonstrates its correlation with Y. My question though is, is there anyway for us to know that what the correlation of x1 values independently, 0 or 1, is with the dependent variable? For instance, do we know if that 0 is the reason for the sign of coefficient and the more 0 will lead to more Y (not sure if this is the correct language but hope you understand what I am saying.)

A real-world example, I have a multiple linear regression model to find the correlation of a set of numeric indexes in tweets, as independent variables, with the number of retweets as dependent variable. One of the independent variables in this model is the tweet's fact checking label, "true" or "false" which we call it "truth_label." I have trained a multiple linear regression model and the coefficient of the truth_label is positive meaning that it has a positive correlation with the number of shares. But, I would like to know if that positive correlation is because of the "true" values or "false" values. Hope this example made my question a bit more clear.

linear-regression correlation

share|improve this question

asked 23 mins ago

PedramPedram

1012

$endgroup$

add a comment | 

$begingroup$

Let's say I have a multiple linear regression model where my dependent variable, Y, is an integer. And, one of my independent variables --x1-- is binary --let's say either 0 or 1.

We know that sign of the coefficient for x1 in the model, positive or negative, demonstrates its correlation with Y. My question though is, is there anyway for us to know that what the correlation of x1 values independently, 0 or 1, is with the dependent variable? For instance, do we know if that 0 is the reason for the sign of coefficient and the more 0 will lead to more Y (not sure if this is the correct language but hope you understand what I am saying.)

A real-world example, I have a multiple linear regression model to find the correlation of a set of numeric indexes in tweets, as independent variables, with the number of retweets as dependent variable. One of the independent variables in this model is the tweet's fact checking label, "true" or "false" which we call it "truth_label." I have trained a multiple linear regression model and the coefficient of the truth_label is positive meaning that it has a positive correlation with the number of shares. But, I would like to know if that positive correlation is because of the "true" values or "false" values. Hope this example made my question a bit more clear.

linear-regression correlation

share|improve this question

asked 23 mins ago

PedramPedram

1012

$endgroup$

share|improve this question

asked 23 mins ago

PedramPedram

1012

share|improve this question

asked 23 mins ago

PedramPedram

1012

asked 23 mins ago

PedramPedram

1012

asked 23 mins ago

PedramPedram

1012